Question

我项目的任务之一是加载数据集（chars74k）并为每个图像设置标签。在这个实现中，我已经有一个包含其他图像的矩阵和一个带有各自标签的列表。为了完成任务，我编写了以下代码：

#images: (input/output)matrix of images
#labels: (input/output)list of labels
#path:   (input)path to my root folder of images. It is like this:
# path
#   |-folder1
#   |-folder2
#   |-folder3
#   |-...
#   |-lastFolder

def loadChars74k(images, labels, path):
    # list of directories
    dirlist = [ item for item in os.listdir(path) if os.path.isdir(os.path.join(path, item)) ]

    # for each subfolder, open all files, append to list of images x and set path as label in y
    for subfolder in dirlist:   
        imagePath = glob.glob(path + '/' + subfolder +'/*.Bmp')
        print "folder ", subfolder, " has ",len(imagePath), " images and matrix of images is:", images.shape, "labels are:", len(labels)
        for i in range(len(imagePath)):
            anImage = numpy.array(Image.open(imagePath[i]).convert('L'), 'f').ravel()
            images = numpy.vstack((images,anImage))
            labels.append(subfolder)

它工作正常，但耗时太长（大约20分钟）。我想知道是否有更快的方法来加载图像和设置标签。

问候。

Answer 1

经过一番研究，我能够以这种方式改进代码：

def loadChars74k(images, labels, path):
    # list of directories
    dirlist = [ item for item in os.listdir(path) if os.path.isdir(os.path.join(path, item)) ]

    # for each subfolder, open all files, append to list of images x and set path as label in y
    for subfolder in dirlist:   
        imagePath = glob.glob(path + '/' + subfolder +'/*.Bmp')
        im_array = numpy.array( [numpy.array(Image.open(imagePath[i]).convert('L'), 'f').ravel() for i in range(len(imagePath))] )
        images = numpy.vstack((images, im_array))
        for i in range(len(imagePath)):
            labels.append(subfolder)

    return images, labels

我很确定它可以进一步提高，但现在还可以！它现在花了33秒！

Python - 加载多个图像的更快方法？

1 个答案: